Data Engineer

Data Engineer

Requirements

• Strong understanding of ETL fundamentals and modern data engineering principles.
• Expertise in SQL (both basic and advanced), PLSQL, and T-SQL.
• Experience with Google Cloud Platform services: BigQuery, Dataflow, Dataproc, Data Fusion, Cloud Composer, Cloud Trace, Cloud Logging, Cloud Storage, Data Catalog.
• Proficiency in Python for data engineering tasks and automation.
• Solid understanding of data warehousing and data modeling practices.
• Experience building pipelines in a modern data platform environment.

Responsibilities

• Design, develop, and maintain scalable ETL pipelines for structured and unstructured data.
• Write and optimize complex SQL queries (Basic + Advanced) to support analytics and reporting.
• Work with Google Big Query for data warehousing, transformation, and performance optimization.
• Develop distributed data processing solutions using Dataproc, Dataflow, and Data Fusion.
• Orchestrate data workflows using Cloud Composer (Airflow).
• Implement logging and monitoring using Cloud Trace, Cloud Logging, and Cloud Storage.
• Build and maintain metadata repositories with Data Catalog for effective data governance.
• Apply strong data modelling fundamentals for designing normalized and denormalized data structures.
• Collaborate with cross-functional teams to implement modern data platform fundamentals.
• Write and manage stored procedures using PLSQL, T-SQL, and other scripting tools.
• Leverage Python for scripting, automation, and data manipulation tasks.
• Ensure data quality, accuracy, and performance across all data platforms.

Preferred Qualifications

• GCP certification (e.g., Professional Data Engineer or equivalent).
• Experience with CI/CD practices in data engineering.
• Familiarity with other cloud platforms (AWS, Azure) is a plus.
• Exposure to data security and governance practices.